Data- and model-domain up/down wave separation for reverse-time migration with free-surface multiples

2020 ◽  
Vol 223 (1) ◽  
pp. 77-93
Author(s):  
Peng Guo ◽  
Huimin Guan ◽  
George A McMechan

SUMMARY Seismic data recorded using a marine acquisition geometry contain both upgoing reflections from subsurface structures and downgoing ghost waves reflected back from the free surface. In addition to the ambiguity of propagation directions in the data, using the two-way wave equation for wavefield extrapolation of seismic imaging generates backscattered/turned waves when there are strong velocity contrasts/gradients in the model, which further increases the wavefield complexity. For reverse-time migration (RTM) of free-surface multiples, apart from unwanted crosstalk between inconsistent orders of reflections, image artefacts can also be formed along with the true reflector images from the overlapping of up/downgoing waves in the data and in the extrapolated wavefield. We present a wave-equation-based, hybrid (data- and model-domain) wave separation workflow, with vector seismic data containing pressure- and vertical-component particle velocity from dual-sensor seismic acquisition, for removing image artefacts produced by the mixture of up/downgoing waves. For imaging with free-surface multiples, the wavefield extrapolated from downgoing ghost events (reflected from the free surface) in the recorded data act as an effective source wavefield for one-order-higher free-surface multiples. Therefore, only the downgoing waves in the data should be used as the source wavefield for RTM with multiples; the recorded upgoing waves in the seismograms will be used for extrapolation of the time-reversed receiver wavefield. We use finite-difference (FD) injection for up/down separation in the data domain, to extrapolate the down- and upgoing waves of the common-source gathers for source and receiver wavefield propagation, respectively. The model-domain separation decomposes the extrapolated wavefield into upgoing (backscattered) and downgoing (transmitted) components at each subsurface grid location, to remove false images produced by cross-correlating backscattered waves along unphysical paths. We combine FD injection with the model-domain wavefield separation, for separating the wavefield into up- and downgoing components for the recorded data and for the extrapolated wavefields. Numerical examples using a simple model, and the Sigsbee 2B model, demonstrate that the hybrid up/down separation approach can effectively produce seismic images of free-surface multiples with better resolution and fewer artefacts.

2021 ◽  
Author(s):  
Hala Alqatari ◽  
Thierry-Laurent Tonellot ◽  
Mohammed Mubarak

Abstract This work presents a full waveform sonic (FWS) dataset processing to generate high-resolution images of the near-borehole area. The dataset was acquired in a nearly horizontal well over a distance of 5400 feet. Multiple formation boundaries can be identified on the final image and tracked at up to 200 feet deep, along the wellbore's trajectory. We first present a new preprocessing sequence to prepare the sonic data for imaging. This sequence leverages denoising algorithms used in conventional surface seismic data processing to remove unwanted components of the recorded data that could harm the imaging results. We then apply a reverse time migration algorithm to the data at different processing stages to assess the impact of the main processing steps on the final image.


Geophysics ◽  
1997 ◽  
Vol 62 (3) ◽  
pp. 906-917 ◽  
Author(s):  
Jinming Zhu ◽  
Larry R. Lines

Reverse‐time migration applies finite‐difference wave equation solutions by using unaliased time‐reversed recorded traces as seismic sources. Recorded data can be sparsely or irregularly sampled relative to a finely spaced finite‐difference mesh because of the nature of seismic acquisition. Fortunately, reliable interpolation of missing traces is implicitly included in the reverse‐time wave equation computations. This implicit interpolation is essentially based on the ability of the wavefield to “heal itself” during propagation. Both synthetic and real data examples demonstrate that reverse‐time migration can often be performed effectively without the need for explicit interpolation of missing traces.


Geophysics ◽  
2019 ◽  
Vol 84 (4) ◽  
pp. S317-S327 ◽  
Author(s):  
Pengfei Yu ◽  
Jianhua Geng

Quasi-P (qP)-wave separation and receiver-side records back extrapolation are two key technologies commonly applied in vertical transverse isotropic (VTI) media for ocean-bottom 4C seismic data pseudoacoustic-wave reverse time migration (RTM). However, it remains problematic to quickly and accurately separate the qP-wave in VTI media. The qP-wave can be fast separated by synthesizing pressure in weakly anisotropic media. Like the derivation of acoustic-elastic coupled equations (AECEs) in an isotropic medium, novel AECEs can also be obtained in VTI media. Based on these novel coupled equations, we have developed a method for pseudoacoustic-wave RTM of ocean-bottom 4C seismic data. Three synthetic examples are provided to illustrate the validity and effectiveness of our method. The results indicate that our method possesses three advantages for ocean-bottom 4C data compared with the conventional method when conducting pseudoacoustic-wave RTM in VTI media. First, these new coupled equations are able to obtain a qP-wave during wavefield propagation. Second, ocean-bottom 4C records can be implemented strictly for receiver-side tensorial extrapolation with undulating topography of the seafloor, which brings benefits for suppressing artifacts in pseudoacoustic-wave RTM and improving imaging quality. Finally, our method is fairly robust to coarse sampling.


Geophysics ◽  
2014 ◽  
Vol 79 (6) ◽  
pp. T287-T300 ◽  
Author(s):  
Lasse Amundsen ◽  
Johan O. A. Robertsson

Methods for wavefield injection are used in, for instance, reverse time extrapolation of shot gathers in reverse time migration. For correct injection of recorded data without any ambiguity of the propagation direction, the wavefield-injection methodology requires pressure and particle velocity data such as multicomponent towed marine or seabed seismic recordings. We discovered that by carefully considering the models (medium parameters and boundary conditions) for injection, wavefield injection of multicomponent data can also be used to solve several long-standing challenges in marine seismic data processing by means of conventional time-space-domain finite-difference propagators. We outlined and demonstrated several of these important applications including up-down separation of wavefields (deghosting), direct-wave removal, source-signature estimation, multiple removal, and imaging using primaries and multiples. Only acoustic models are considered, but the concepts are straightforward to generalize to elastodynamic and electromagnetic models.


Geophysics ◽  
2019 ◽  
Vol 84 (3) ◽  
pp. S171-S185 ◽  
Author(s):  
Chuang Li ◽  
Jianping Huang ◽  
Zhenchun Li ◽  
Han Yu ◽  
Rongrong Wang

Least-squares migration (LSM) of seismic data is supposed to produce images of subsurface structures with better quality than standard migration if we have an accurate migration velocity model. However, LSM suffers from data mismatch problems and migration artifacts when noise pollutes the recorded profiles. This study has developed a reweighted least-squares reverse time migration (RWLSRTM) method to overcome the problems caused by such noise. We first verify that spiky noise and free-surface multiples lead to the mismatch problems and should be eliminated from the data residual. The primary- and multiple-guided weighting matrices are then derived for RWLSRTM to reduce the noise in the data residual. The weighting matrices impose constraints on the data residual such that spiky noise and free-surface multiple reflections are reduced whereas primary reflections are preserved. The weights for spiky noise and multiple reflections are controlled by a dynamic threshold parameter decreasing with iterations for better results. Finally, we use an iteratively reweighted least-squares algorithm to minimize the weighted data residual. We conduct numerical tests using the synthetic data and compared the results of this method with the results of standard LSRTM. The results suggest that RWLSRTM is more robust than standard LSRTM when the seismic data contain spiky noise and multiple reflections. Moreover, our method not only suppresses the migration artifacts, but it also accelerates the convergence.


2021 ◽  
Vol 11 (7) ◽  
pp. 3010
Author(s):  
Hao Liu ◽  
Xuewei Liu

The lack of an initial condition is one of the major challenges in full-wave-equation depth extrapolation. This initial condition is the vertical partial derivative of the surface wavefield and cannot be provided by the conventional seismic acquisition system. The traditional solution is to use the wavefield value of the surface to calculate the vertical partial derivative by assuming that the surface velocity is constant. However, for seismic exploration on land, the surface velocity is often not uniform. To solve this problem, we propose a new method for calculating the vertical partial derivative from the surface wavefield without making any assumptions about the surface conditions. Based on the calculated derivative, we implemented a depth-extrapolation-based full-wave-equation migration from topography using the direct downward continuation. We tested the imaging performance of our proposed method with several experiments. The results of the Marmousi model experiment show that our proposed method is superior to the conventional reverse time migration (RTM) algorithm in terms of imaging accuracy and amplitude-preserving performance at medium and deep depths. In the Canadian Foothills model experiment, we proved that our method can still accurately image complex structures and maintain amplitude under topographic scenario.


Geophysics ◽  
2021 ◽  
pp. 1-65
Author(s):  
Yingming Qu ◽  
Yixin Wang ◽  
Zhenchun Li ◽  
Chang Liu

Seismic wave attenuation caused by subsurface viscoelasticity reduces the quality of migration and the reliability of interpretation. A variety of Q-compensated migration methods have been developed based on the second-order viscoacoustic quasidifferential equations. However, these second-order wave-equation-based methods are difficult to handle with density perturbation and surface topography. In addition, the staggered grid scheme, which has an advantage over the collocated grid scheme because of its reduced numerical dispersion and enhanced stability, works in first-order wave-equation-based methods. We have developed a Q least-squares reverse time migration method based on the first-order viscoacoustic quasidifferential equations by deriving Q-compensated forward-propagated operators, Q-compensated adjoint operators, and Q-attenuated Born modeling operators. Besides, our method using curvilinear grids is available even when the attenuating medium has surface topography and can conduct Q-compensated migration with density perturbation. The results of numerical tests on two synthetic and a field data sets indicate that our method improves the imaging quality with iterations and produces better imaging results with clearer structures, higher signal-to-noise ratio, higher resolution, and more balanced amplitude by correcting the energy loss and phase distortion caused by Q attenuation. It also suppresses the scattering and diffracted noise caused by the surface topography.


2014 ◽  
Vol 962-965 ◽  
pp. 2984-2987
Author(s):  
Jia Jia Yang ◽  
Bing Shou He ◽  
Ting Chen

Based on two-way acoustic wave equation, we present a method for computing angle-domain common-image gathers for reverse time migration. The method calculates the propagation direction of source wave-fields and receiver wave-fields according to expression of energy flow density vectors (Poynting vectors) of acoustic wave equation in space-time domain to obtain the reflection angle, then apply the normalized cross-correlation imaging condition to achieve the angle-domain common-image gathers. The angle gathers obtained can be used for migration velocity analysis, AVA analysis and so on. Numerical examples and real data examples demonstrate the effectiveness of this method.


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